Virtual encounters have experienced an exponential rise amid the current COVID-19 crisis. This abrupt change, seen in response to unprecedented medical and environmental challenges, has been forced upon the orthopaedic community. However, such changes to adopting virtual care and technology were already in the evolution forecast, albeit in an unpredictable timetable impeded by regulatory and financial barriers. This adoption is not meant to replace, but rather augment established, traditional
Aims. The aims of this study were to describe the demographic, socioeconomic, and educational factors associated with core surgical trainees (CSTs) who apply to and receive offers for higher surgical training (ST3) posts in Trauma & Orthopaedics (T&O). Methods. Data collected by the UK Medical Education Database (UKMED) between 1 January 2014 and 31 December 2019 were used in this retrospective longitudinal cohort study comprising 1,960 CSTs eligible for ST3. The primary outcome measures were whether CSTs applied for a T&O ST3 post and if they were subsequently offered a post. A directed acyclic graph was used for detecting confounders and adjusting logistic regression
Aims. The primary aim is to estimate the current and potential number of patients on NHS England orthopaedic elective waiting lists by November 2020. The secondary aims are to
The response to the COVID-19 pandemic has raised the profile and level of interest in the use, acceptability, safety, and effectiveness of virtual outpatient consultations and telemedicine. These
Aims. Restarting planned surgery during the COVID-19 pandemic is a clinical and societal priority, but it is unknown whether it can be done safely and include high-risk or complex cases. We developed a Surgical Prioritization and Allocation Guide (SPAG). Here, we validate its effectiveness and safety in COVID-free sites. Methods. A multidisciplinary surgical prioritization committee developed the SPAG, incorporating procedural urgency, shared decision-making, patient safety, and biopsychosocial factors; and applied it to 1,142 adult patients awaiting orthopaedic surgery. Patients were stratified into four priority groups and underwent surgery at three COVID-free sites, including one with access to a high dependency unit (HDU) or intensive care unit (ICU) and specialist resources. Safety was assessed by the number of patients requiring inpatient postoperative HDU/ICU admission, contracting COVID-19 within 14 days postoperatively, and mortality within 30 days postoperatively. Results. A total of 1,142 patients were included, 47 declined surgery, and 110 were deemed high-risk or requiring specialist resources. In the ten-week study period, 28 high-risk patients underwent surgery, during which 68% (13/19) of Priority 2 (P. 2. , surgery within one month) patients underwent surgery, and 15% (3/20) of P. 3. (< three months) and 16% (11/71) of P. 4. (> three months) groups. Of the 1,032 low-risk patients, 322 patients underwent surgery. Overall, 21 P. 3. and P. 4. patients were expedited to ‘Urgent’ based on biopsychosocial factors identified by the SPAG. During the study period, 91% (19/21) of the Urgent group, 52% (49/95) of P. 2. , 36% (70/196) of P. 3. , and 26% (184/720) of P. 4. underwent surgery. No patients died or were admitted to HDU/ICU, or contracted COVID-19. Conclusion. Our widely generalizable
Aims. The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML)
Aims. Elective operating was halted during the COVID-19 pandemic to increase the capacity to provide care to an unprecedented volume of critically unwell patients. During the pandemic, the orthopaedic department at the Aneurin Bevan University Health Board restructured the trauma service, relocating semi-urgent ambulatory trauma operating to the isolated clean elective centre (St. Woolos’ Hospital) from the main hospital receiving COVID-19 patients (Royal Gwent Hospital). This study presents our experience of providing semi-urgent trauma care in a COVID-19-free surgical unit as a safe way to treat trauma patients during the pandemic and a potential
Aims. Currently, there is no single, comprehensive national guideline for analgesic strategies for total joint replacement. We compared inpatient and outpatient opioid requirements following total hip arthroplasty (THA) versus total knee arthroplasty (TKA) in order to determine risk factors for increased inpatient and outpatient opioid requirements following total hip or knee arthroplasty. Methods. Outcomes after 92 primary total knee (n = 49) and hip (n = 43) arthroplasties were analyzed. Patients with repeat surgery within 90 days were excluded. Opioid use was recorded while inpatient and 90 days postoperatively. Outcomes included total opioid use, refills, use beyond 90 days, and unplanned clinical encounters for uncontrolled pain. Multivariate
Aims. Medical comorbidities are a critical factor in the decision-making process for operative management and risk-stratification. The Hierarchical Condition Categories (HCC) risk adjustment
Aims. To assess if older symptomatic children with club foot deformity differ in perceived disability and foot function during gait, depending on initial treatment with Ponseti or surgery, compared to a control group. Second aim was to investigate correlations between foot function during gait and perceived disability in this population. Methods. In all, 73 children with idiopathic club foot were included: 31 children treated with the Ponseti method (mean age 8.3 years; 24 male; 20 bilaterally affected, 13 left and 18 right sides analyzed), and 42 treated with primary surgical correction (mean age 11.6 years; 28 male; 23 bilaterally affected, 18 left and 24 right sides analyzed). Foot function data was collected during walking gait and included Oxford Foot
Aims. Hip fracture patients are at higher risk of severe COVID-19 illness, and admission into hospital puts them at further risk. We implemented a two-site orthopaedic trauma service, with ‘COVID’ and ‘COVID-free’ hubs, to deliver urgent and infection-controlled trauma care for hip fracture patients, while increasing bed capacity for medical patients during the COVID-19 pandemic. Methods. A vacated private elective surgical centre was repurposed to facilitate a two-site, ‘COVID’ and ‘COVID-free’, hip fracture service. Patients were screened for COVID-19 infection and either kept at our ‘COVID’ site or transferred to our ‘COVID-free’ site. We collected data for 30 days on patient demographics, Clinical Frailty Scale (CFS), Nottingham Hip Fracture Scores (NHFS), time to surgery, COVID-19 status, mortality, and length of stay (LOS). Results. In all, 47 hip fracture patients presented to our service: 12 were admitted to the ‘COVID’ site and 35 to the ‘COVID-free’ site. The ‘COVID’ site cohort were older (mean 86.8 vs 78.5 years, p = 0.0427) and with poorer CFS (p = 0.0147) and NHFS (p = 0.0023) scores. At the ‘COVID-free’ site, mean time to surgery was less (29.8 vs 52.8 hours, p = 0.0146), and mean LOS seemed shorter (8.7 vs 12.6 days, p = 0.0592). No patients tested positive for COVID-19 infection while at the ‘COVID-free’ site. We redirected 74% of our admissions from the base ‘COVID’ site and created 304 inpatient days’ capacity for medical COVID patients. Conclusion. Acquisition of unused elective orthopaedic capacity from the private sector facilitated a two-site trauma service. Patients were treated expeditiously, while successfully achieving strict infection control. We achieved significant gains in medical bed capacity in response to the COVID-19 demand. The authors propose the repurposing of unused elective operating facilities for a two-site ‘COVID’ and ‘COVID-free’
Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp).Aims
Methods
It is well described that patients with bone and joint infections (BJIs) commonly experience significant functional impairment and disability. Published literature is lacking on the impact of BJIs on mental health. Therefore, the aim of this study was to assess health-related quality of life (HRQoL) and the impact on mental health in patients with BJIs. The AO Trauma Infection Registry is a prospective multinational registry. In total, 229 adult patients with long-bone BJI were enrolled between 1 November 2012 and 31 August 2017 in 18 centres from ten countries. Clinical outcome data, demographic data, and details on infections and treatments were collected. Patient-reported outcomes using the 36-Item Short-Form Health Survey questionnaire (SF-36), Parker Mobility Score, and Katz Index of Independence in Activities of Daily Living were assessed at one, six, and 12 months. The SF-36 mental component subscales were analyzed and correlated with infection characteristics and clinical outcome.Aims
Methods
The purpose of this survey study was to examine the demographic and lifestyle factors of women currently in orthopaedic surgery. An electronic survey was conducted of practising female orthopaedic surgeons based in the USA through both the Ruth Jackson Society and the online Facebook group “Women of Orthopaedics”.Aims
Methods
The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.Aims
Methods
Early large treatment effects can arise in small studies, which lessen as more data accumulate. This study aimed to retrospectively examine whether early treatment effects occurred for two multicentre orthopaedic randomized controlled trials (RCTs) and explore biases related to this. Included RCTs were ProFHER (PROximal Fracture of the Humerus: Evaluation by Randomisation), a two-arm study of surgery versus non-surgical treatment for proximal humerus fractures, and UK FROST (United Kingdom Frozen Shoulder Trial), a three-arm study of two surgical and one non-surgical treatment for frozen shoulder. To determine whether early treatment effects were present, the primary outcome of Oxford Shoulder Score (OSS) was compared on forest plots for: the chief investigator’s (CI) site to the remaining sites, the first five sites opened to the other sites, and patients grouped in quintiles by randomization date. Potential for bias was assessed by comparing mean age and proportion of patients with indicators of poor outcome between included and excluded/non-consenting participants.Aims
Methods
The evidence base within trauma and orthopaedics has traditionally favoured quantitative research methodologies. Qualitative research can provide unique insights which illuminate patient experiences and perceptions of care. Qualitative methods reveal the subjective narratives of patients that are not captured by quantitative data, providing a more comprehensive understanding of patient-centred care. The aim of this study is to quantify the level of qualitative research within the orthopaedic literature. A bibliometric search of journals’ online archives and multiple databases was undertaken in March 2024, to identify articles using qualitative research methods in the top 12 trauma and orthopaedic journals based on the 2023 impact factor and SCImago rating. The bibliometric search was conducted and reported in accordance with the preliminary guideline for reporting bibliometric reviews of the biomedical literature (BIBLIO).Aims
Methods
Our primary aim was to establish the proportion of female orthopaedic consultants who perform arthroplasty via cases submitted to the National Joint Registry (NJR), which covers England, Wales, Northern Ireland, the Isle of Man, and Guernsey. Secondary aims included comparing time since specialist registration, private practice participation, and number of hospitals worked in between male and female surgeons. Publicly available data from the NJR was extracted on the types of arthroplasty performed by each surgeon, and the number of procedures of each type undertaken. Each surgeon was cross-referenced with the General Medical Council (GMC) website, using GMC number to extract surgeon demographic data. These included sex, region of practice, and dates of full and specialist registration.Aims
Methods
The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID).Aims
Methods
Deprivation underpins many societal and health inequalities. COVID-19 has exacerbated these disparities, with access to planned care falling greatest in the most deprived areas of the UK during 2020. This study aimed to identify the impact of deprivation on patients on growing waiting lists for planned care. Questionnaires were sent to orthopaedic waiting list patients at the start of the UK’s first COVID-19 lockdown to capture key quantitative and qualitative aspects of patients’ health. A total of 888 respondents were divided into quintiles, with sampling stratified based on the Index of Multiple Deprivation (IMD); level 1 represented the ‘most deprived’ cohort and level 5 the ‘least deprived’.Aims
Methods